scholarly journals Application Of A Physiologically-Based Pharmacokinetic (PBPK) Model In Predicting Drug Interactions

2020 ◽  
Vol 6 (1) ◽  
pp. 25
Author(s):  
Maya Radeva-Ilieva ◽  
Kaloyan Georgiev
Keyword(s):  
Drug Interactions ◽  
Pbpk Model ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

scholarly journals Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions

2021 ◽  
Author(s):  
Nina Hanke ◽  
José David Gómez-Mantilla ◽  
Naoki Ishiguro ◽  
Peter Stopfer ◽  
Valerie Nock
Keyword(s):  
Drug Interactions ◽  
Pbpk Model ◽  
Open Systems ◽  
Whole Body ◽  
Good Prediction ◽  
Active Efflux ◽  
Physiologically Based Pharmacokinetic ◽  
Positron Emission ◽  
Physiologically Based

Abstract Purpose To build a physiologically based pharmacokinetic (PBPK) model of the clinical OATP1B1/OATP1B3/BCRP victim drug rosuvastatin for the investigation and prediction of its transporter-mediated drug-drug interactions (DDIs). Methods The Rosuvastatin model was developed using the open-source PBPK software PK-Sim®, following a middle-out approach. 42 clinical studies (dosing range 0.002–80.0 mg), providing rosuvastatin plasma, urine and feces data, positron emission tomography (PET) measurements of tissue concentrations and 7 different rosuvastatin DDI studies with rifampicin, gemfibrozil and probenecid as the perpetrator drugs, were included to build and qualify the model. Results The carefully developed and thoroughly evaluated model adequately describes the analyzed clinical data, including blood, liver, feces and urine measurements. The processes implemented to describe the rosuvastatin pharmacokinetics and DDIs are active uptake by OATP2B1, OATP1B1/OATP1B3 and OAT3, active efflux by BCRP and Pgp, metabolism by CYP2C9 and passive glomerular filtration. The available clinical rifampicin, gemfibrozil and probenecid DDI studies were modeled using in vitro inhibition constants without adjustments. The good prediction of DDIs was demonstrated by simulated rosuvastatin plasma profiles, DDI AUClast ratios (AUClast during DDI/AUClast without co-administration) and DDI Cmax ratios (Cmax during DDI/Cmax without co-administration), with all simulated DDI ratios within 1.6-fold of the observed values. Conclusions A whole-body PBPK model of rosuvastatin was built and qualified for the prediction of rosuvastatin pharmacokinetics and transporter-mediated DDIs. The model is freely available in the Open Systems Pharmacology model repository, to support future investigations of rosuvastatin pharmacokinetics, rosuvastatin therapy and DDI studies during model-informed drug discovery and development (MID3).

scholarly journals Physiologically-Based Pharmacokinetic Modeling for Drug-Drug Interactions of Procainamide and N-Acetylprocainamide with Cimetidine, an Inhibitor of rOCT2 and rMATE1, in Rats

Pharmaceutics ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 108 ◽  
Author(s):  
Yoo-Seong Jeong ◽  
Anusha Balla ◽  
Kwang-Hoon Chun ◽  
Suk-Jae Chung ◽  
Han-Joo Maeng
Keyword(s):  
Urinary Excretion ◽  
Drug Interactions ◽  
Pbpk Model ◽  
Systemic Exposure ◽  
Renal Elimination ◽  
Physiologically Based Pharmacokinetic ◽  
Pharmacokinetic Interactions ◽  
Physiologically Based

Previous observations demonstrated that cimetidine decreased the clearance of procainamide (PA) and/or N-acetylprocainamide (NAPA; the primary metabolite of PA) resulting in the increased systemic exposure and the decrease of urinary excretion. Despite an abundance of in vitro and in vivo data regarding pharmacokinetic interactions between PA/NAPA and cimetidine, however, a mechanistic approach to elucidate these interactions has not been reported yet. The primary objective of this study was to construct a physiological model that describes pharmacokinetic interactions between PA/NAPA and cimetidine, an inhibitor of rat organic cation transporter 2 (rOCT2) and rat multidrug and toxin extrusion proteins (rMATE1), by performing extensive in vivo and in vitro pharmacokinetic studies for PA and NAPA performed in the absence or presence of cimetidine in rats. When a single intravenous injection of PA HCl (10 mg/kg) was administered to rats, co-administration of cimetidine (100 mg/kg) significantly increased systemic exposure and decreased the systemic (CL) and renal (CLR) clearance of PA, and reduced its tissue distribution. Similarly, cimetidine significantly decreased the CLR of NAPA formed by the metabolism of PA and increased the AUC of NAPA. Considering that these drugs could share similar renal secretory pathways (e.g., via rOCT2 and rMATE1), a physiologically-based pharmacokinetic (PBPK) model incorporating semi-mechanistic kidney compartments was devised to predict drug-drug interactions (DDIs). Using our proposed PBPK model, DDIs between PA/NAPA and cimetidine were successfully predicted for the plasma concentrations and urinary excretion profiles of PA and NAPA observed in rats. Moreover, sensitivity analyses of the pharmacokinetics of PA and NAPA showed the inhibitory effects of cimetidine via rMATE1 were probably important for the renal elimination of PA and NAPA in rats. The proposed PBPK model may be useful for understanding the mechanisms of interactions between PA/NAPA and cimetidine in vivo.

scholarly journals Development of Physiologically Based Pharmacokinetic Model for Orally Administered Fexuprazan in Humans

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 813
Author(s):  
Yoo-Seong Jeong ◽  
Min-Soo Kim ◽  
Nora Lee ◽  
Areum Lee ◽  
Yoon-Jee Chae ◽  
...  
Keyword(s):  
Gastric Acid ◽  
Pbpk Model ◽  
Pbpk Modeling ◽  
Drug Candidate ◽  
Metabolite Formation ◽  
Pbpk Models ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Fexuprazan is a new drug candidate in the potassium-competitive acid blocker (P-CAB) family. As proton pump inhibitors (PPIs), P-CABs inhibit gastric acid secretion and can be used to treat gastric acid-related disorders such as gastroesophageal reflux disease (GERD). Physiologically based pharmacokinetic (PBPK) models predict drug interactions as pharmacokinetic profiles in biological matrices can be mechanistically simulated. Here, we propose an optimized and validated PBPK model for fexuprazan by integrating in vitro, in vivo, and in silico data. The extent of fexuprazan tissue distribution in humans was predicted using tissue-to-plasma partition coefficients in rats and the allometric relationships of fexuprazan distribution volumes (VSS) among preclinical species. Urinary fexuprazan excretion was minimal (0.29–2.02%), and this drug was eliminated primarily by the liver and metabolite formation. The fraction absorbed (Fa) of 0.761, estimated from the PBPK modeling, was consistent with the physicochemical properties of fexuprazan, including its in vitro solubility and permeability. The predicted oral bioavailability of fexuprazan (38.4–38.6%) was within the range of the preclinical datasets. The Cmax, AUClast, and time-concentration profiles predicted by the PBPK model established by the learning set were accurately predicted for the validation sets.

scholarly journals 1315. No Dose Adjustment of Metformin with Fostemsavir Coadministration Based on Mechanistic Static and Physiologically Based Pharmacokinetic Models

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S669-S669
Author(s):  
Dung N Nguyen ◽  
Xiusheng Miao ◽  
Mindy Magee ◽  
Guoying Tai ◽  
Peter D Gorycki ◽  
...  
Keyword(s):  
Dose Adjustment ◽  
Pbpk Model ◽  
Systemic Exposure ◽  
Multidrug Resistant ◽  
Pbpk Modeling ◽  
Repeat Dose ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

Abstract Background Fostemsavir (FTR) is an oral prodrug of the first-in-class attachment inhibitor temsavir (TMR) which is being evaluated in patients with multidrug resistant HIV-1 infection. In vitro studies indicated that TMR and its 2 major metabolites are inhibitors of organic cation transporters (OCT)1, OCT2, and multidrug and toxin extrusion transporters (MATEs). To assess the clinical relevance, of OCT and MATE inhibition, mechanistic static DDI prediction with calculated Imax,u/IC50 ratios was below the cut-off limits for a DDI flag based on FDA guidelines and above the cut-off limits for MATEs based on EMA guidelines. Methods Metformin is a commonly used probe substrate for OCT1, OCT2 and MATEs. To predict the potential for a drug interaction between TMR and metformin, a physiologically based pharmacokinetic (PBPK) model for TMR was developed based on its physicochemical properties, in vitro and in vivo data. The model was verified and validated through comparison with clinical data. The TMR PBPK model accurately described AUC and Cmax within 30% of the observed data for single and repeat dose studies with or without food. The SimCYP models for metformin and ritonavir were qualified using literature data before applications of DDI prediction for TMR Results TMR was simulated at steady state concentrations after repeated oral doses of FTR 600 mg twice daily which allowed assessment of the potential OCT1, OCT2, and MATEs inhibition by TMR and metabolites. No significant increase in metformin systemic exposure (AUC or Cmax) was predicted with FTR co-administration. In addition, a sensitivity analysis was conducted for either hepatic OCT1 Ki, or renal OCT2 and MATEs Ki values. The model output indicated that, a 10-fold more potent Ki value for TMR would be required to have a ~15% increase in metformin exposure Conclusion Based on mechanistic static models and PBPK modeling and simulation, the OCT1/2 and MATEs inhibition potential of TMR and its metabolites on metformin pharmacokinetics is not clinically significant. No dose adjustment of metformin is necessary when co-administered with FTR Disclosures Xiusheng Miao, PhD, GlaxoSmithKline (Employee) Mindy Magee, Doctor of Pharmacy, GlaxoSmithKline (Employee, Shareholder) Peter D. Gorycki, BEChe, MSc, PhD, GSK (Employee, Shareholder) Katy P. Moore, PharmD, RPh, ViiV Healthcare (Employee)

scholarly journals Physiologically Based Pharmacokinetic Model of Rifapentine and 25-Desacetyl Rifapentine Disposition in Humans

2016 ◽  
Vol 60 (8) ◽  
pp. 4860-4868
Author(s):  
Todd J. Zurlinden ◽  
Garrett J. Eppers ◽  
Brad Reisfeld
Keyword(s):  
Time Course ◽  
Pbpk Model ◽  
Plasma Concentrations ◽  
Optimal Dose ◽  
Tissue Level ◽  
Pharmacokinetic Data ◽  
Rat Tissues ◽  
Content Type ◽  
Physiologically Based Pharmacokinetic ◽  
Physiologically Based

ABSTRACTRifapentine (RPT) is a rifamycin antimycobacterial and, as part of a combination therapy, is indicated for the treatment of pulmonary tuberculosis (TB) caused byMycobacterium tuberculosis. Although the results from a number of studies indicate that rifapentine has the potential to shorten treatment duration and enhance completion rates compared to other rifamycin agents utilized in antituberculosis drug regimens (i.e., regimens 1 to 4), its optimal dose and exposure in humans are unknown. To help inform such an optimization, a physiologically based pharmacokinetic (PBPK) model was developed to predict time course, tissue-specific concentrations of RPT and its active metabolite, 25-desacetyl rifapentine (dRPT), in humans after specified administration schedules for RPT. Starting with the development and verification of a PBPK model for rats, the model was extrapolated and then tested using human pharmacokinetic data. Testing and verification of the models included comparisons of predictions to experimental data in several rat tissues and time course RPT and dRPT plasma concentrations in humans from several single- and repeated-dosing studies. Finally, the model was used to predict RPT concentrations in the lung during the intensive and continuation phases of a current recommended TB treatment regimen. Based on these results, it is anticipated that the PBPK model developed in this study will be useful in evaluating dosing regimens for RPT and for characterizing tissue-level doses that could be predictors of problems related to efficacy or safety.

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